The automotive industry is undergoing radical change. Volatile markets, geopolitical uncertainties, new entrants and technological disruption are reshaping the demands placed on marketing. Today’s automotive marketing must be smart, scalable and data-driven. The type of data architecture required – and how data can be harnessed in marketing – depends largely on the manufacturer’s market position.
Modern automotive marketing is comparable to semi-autonomous driving: the human remains at the wheel – yet millions of data points in the background keep the campaign, and thus the company’s success, on track. First-party data and broader market insights are indispensable. Only those manufacturers that systematically collect, refine and secure their data can free themselves from external platforms in the long term and build scalable business models of their own.
But which data are decisive? And how can they be deployed profitably? The answer depends on the market and brand profile: established player or challenger? Combustion engine or electric model? Premium segment or volume market? Private buyers or fleet customers? Ultimately, the key question remains the same: not simply “Who holds the data?” but “Who uses them with strategic effectiveness and confidence?”
Data as the Navigator in New Markets
Entering a new geographical market poses particular challenges for carmakers. In newcomer status, reliable first-party data are often scarce. Consumer behaviour, media usage and audience segments differ from the home market – past insights are missing and familiar mechanisms no longer apply.
At this stage, the focus must be on systematically unlocking data. External sources such as market studies, mobility statistics, purchasing power analyses or media usage patterns provide an initial orientation. At the same time, early campaigns can be designed to generate not just reach but also actionable insights into user behaviour – for instance through test markets, A/B testing or regional rollouts.
The goal here is to generate reliable hypotheses on audiences, channels and messaging with manageable effort, and then refine marketing measures iteratively on a data-driven basis. Above all, this approach enables rapid learning while reducing risk.
Established Markets: Connecting and Activating Data
Established brands, by contrast, operate with an entirely different data reality – and with different objectives. Their strategy is less about breadth and more about depth. Vast amounts of data are typically available, but often fragmented across numerous silos, both internal and external: CRM systems, digital touchpoints, dealer reports, media and after-sales data – frequently in incompatible formats and systems used in isolation by different business units.
Carmakers usually know who their customers are, which vehicle they drive and when their lease expires. The challenge is not collecting the data but orchestrating and activating it – across channels and in an automated way. Harmonised data models, central dashboards and integrated reporting structures that span all stakeholders help connect relevant sources. This provides the basis for more precise targeting, more efficient budget management and, crucially, measurable advertising effectiveness.
Data Architecture as Strategic Advantage
In the automotive sector, data emerge from highly diverse sources – from online configurators to CRM systems to connected cars. The ability to cluster these data purposefully and assess them for marketing and sales potential is becoming a decisive competitive advantage.
Integrated, data-driven and international campaign planning and media strategy also require linking a wide range of external datasets via an intelligent data architecture. These include market data, live performance data from ongoing campaigns and media ROI. Another important lever is integrating campaign and order data from the manufacturer. This makes it possible to reveal direct correlations between media performance and sales, and to continuously optimise campaigns.
Many manufacturers, however, hesitate to bring operational sales data into marketing – due to privacy concerns or systemic complexity. Yet with the right data architecture and privacy-by-design principles, these hurdles can be overcome.
Why Decentralisation Matters: The Data Mesh Principle
A modern approach to data organisation is the concept of Data Mesh. This decentralised model allows data to remain with brands, markets and agencies – while still being accessible via shared standards and interfaces. In this way, data sovereignty is preserved without sacrificing synergies.
Ideally, this includes data from all funnel stages – from awareness through to relevance and conversion. An AI-driven algorithm can then calculate the most efficient media mix from millions of combinations.
Dashboards as the Basis for Optimisation
What the cockpit is to the driver, the central dashboard is to the marketer: a control centre for data-driven marketing. It consolidates all relevant information – from media performance and audience reactions to budget flows – forming the foundation for precise decision-making.
As each manufacturer prioritises different KPIs, dashboards must be tailored individually. Alongside short-term metrics from digital channels, long-term brand indicators such as awareness or affinity are also essential – particularly for evaluating brandformance strategies that combine performance with branding activities.
A strong TV campaign that drives online research and touchpoints, for instance, can significantly enhance the efficiency of digital retargeting. Integrated dashboards that reflect both worlds provide real added value.
Making Data Competence Scalable – for Clients and Agencies
In times of sales pressure and high volatility, data-driven working is becoming a central success factor. It is therefore all the more important that the insights gained are shared within organisations – both among manufacturers and across their agencies.
Setting up a central hub for collecting and distributing campaign insights is essential. This makes it possible to scale successes internationally, shorten optimisation cycles and deploy budgets more efficiently.
Take dynamic creative generation as an example: producing bespoke assets for every model and audience segment is technically feasible – but expensive. In practice, scaled creatives designed for global use often deliver better results with lower effort.
Taxonomy: The Foundation of Every Data Strategy
To use data effectively, they must first be captured correctly – particularly in international structures. Different naming conventions quickly lead to inconsistent data collection and errors in reporting. It may sound trivial, but at global scale it is anything but. If several colleagues work on a campaign with different filing logics, files and links for the same activity may carry inconsistent labels – making accurate monitoring and control difficult.
With dedicated taxonomy software (the “OneBuilder”), banners, assets and links can be named consistently – eliminating individual interpretation. This ensures that tracking and attribution of campaign materials are reliable, and that insights can be retrieved across markets at the push of a button in real time.
Conclusion: Data Strategy is Not Optional – It’s Essential
Automotive marketing is complex – and data-driven working is no longer a nice-to-have but a fundamental requirement. Whether entering new markets or operating in mature ones: only those who structure their data intelligently, organise it in a decentralised way and activate it operationally will secure sustainable efficiency, impact and differentiation.
This article was first published in Horizont.
